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Mean Intersection-Over-Union is a common evaluation metric for semantic image
segmentation, which first computes the IOU for each semantic class and then
computes the average over classes. IOU is defined as follows:
IOU = true_positive / (true_positive + false_positive + false_negative).
The predictions are accumulated in a confusion matrix, weighted by
sample_weight and the metric is then calculated from it.

If sample_weight is None, weights default to 1.
Use sample_weight of 0 to mask values.